• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.4
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• pp.442-450
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• 2008

In this paper, the phase diverisity in a direct-conversion receiver for a UHF RFID reader is analyzed and the optimal I/Q signal combining methods is presented with respect to tag modulation. At first, fading characteristics of a single channel receiver is shown to prove the importance of phase diversity due to the phase relationship between the backscattered signal and the local oscillator. And the optimal signal combining methods are presented in order to overcome the signal power reduction due to phase diversity. In case of ASK, the power combining method is presented for the optimal I/Q combining. And the arctangent and principal component combining methods using covariance matrix of I and Q channels are presented for the optimal I/Q combining in case of PSK. In order to analyze the performance of suggested methods, the selection diversity and the optimal combining methods are compared. According to analysis and simulation results, the optimal combining methods have a maximum 3 dB SNR enhancement than selection diversity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.446-452
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• 2009

OFDM system has a disadvantage of sensitiveness about the effect of frequency offset caused by the discord of oscillators in the transmitter and receiver. Either, the frequency offsets in mobile radio channels distort the orthogonality between sub-carriers resulting in the inter-carrier interference(ICI). In this paper, we analyze the effect of the ICI and propose a new method using SC technique. To analyze BER(Bit Error Rate) and CIR(Carrier to Interference Ratio) performance of the proposed method. the simulation program MATLAB is used. By the simulation results, SNR performance is improved by this method. In case the frequency offset is 0.3 and 0.5, SNR gains are over 0.5dB and 1dB in the BPSK modulation and 1dB and 2dB in the QPSK modulation at BER of $10^{-3}$ respectively. In addition, CIR performance is improved over 15dB. As a result, the proposed method is more effective to improve the system performance than the conventional method.

• Journal of Sensor Science and Technology
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• v.18 no.6
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• pp.423-431
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• 2009

Standard uroflowmetry measures the urine weight using single load cell to evaluate the urinary flow rate. Impact noise should be introduced due to gravity when the urine stream falls down into the container upon the load cell. The present study placed three load cells on the three vertices of a regular triangle and the three signals were ensemble averaged to enhance the signal-to-noise ratio(SNR) regardless of how the urination was made. Simulated urination experiment was performed with three different urine collection methods. In all three methods, SNR of the averaged signal was much higher than each load cell signals. With no urine collection device, the present signal averaging technique resulted in SNR values higher by 10~15 dB than when dual funnels or upper funnel were used to guide the urine stream. Therefore, it was demonstrated that the three point measurement followed by with ensemble averaging could enable accurate uroflowmetric test without any specially made urine collection devices.

• Korean Journal of Digital Imaging in Medicine
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• v.17 no.1
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• pp.33-41
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• 2015

This study attempts to examine the clinical usefulness of High b-value DWI (diffusion weighted imaging) for brain tumors with an edema. Subjects were seven patients selected from 65 patients who received an MRI scan for suspected encephalopathy and confirmed diagnosis at our hospital from February to July 2015 (male: 7, average age : 66 years old). As test equipment, 3.0T MR System (ACHIEVA Release, Philips, Best, The Netherlands) and 8Channel SENSE Head Coill were used. DWI checks on the use of the variable TR 5460ms, TE 132ms, Slice Thickness 4mm, gap 1mm, Slice number 29 is, 3D T1WI is TR 8.4ms, TE 3.9ms, matrix size $240{\times}240$, Slice can set 180 piecesIt was. b value of 0, 1,000, 2,000 s/mm2 with DWI acquisition and 3D T1WI enhancement five minutes after the Slice Thickness 3mm, gap 0mm to reconstruct the upper face axis (MPR TRA CE) was. As for the experiment, in b-value 1,000 and 2,000 images, SNR and the lesion at the lesion site and CNR in the normal site opposite to the lesion are measured. WW(window width) and WL(window level) are made equal in MRICro software, and the volume of the lesion is measured from each of b-value and MPR TRA CE image. Using SPSS ver. 1.8.0.0 Mann Whitney-test was analyzed for SNR and CNR, while Kruskal-Wallis test was analyzed for volume.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.104-111
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• 2012

In this paper, we propose a novel method to improve the performance of the improved minima controlled recursive averaging (IMCRA). From an examination for various noise environment, it is shown that the IMCRA has a fundamental drawback for the noise power estimate at the offset region of continuity speech signals. Espectially, it is difficult to obtain the robust estimates of the noise power in non-stationary noisy environments that is rapidly changed the spectral characteristics such as babble noise. To overcome the drawback, we apply the global speech absence probability (GSAP) conditioned on both a priori SNR and a posteriori SNR to the speech detection algorithm of IMCRA. With the performance criteria of the ITU-T P.862 perceptual evaluation of speech quality (PESQ) and a composite measure test, we show that the proposed algorithm yields better results compared to the conventional IMCRA-based scheme under various noise environments. In particular, in the case of babble 5 dB, the proposed method produced a remarkable improvement compared to the IMCRA ( PESQ = 0.026, composite measure = 0.029 ).

• Journal of Yeungnam Medical Science
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• v.37 no.2
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• pp.90-97
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• 2020

Background: To minimize damage to the ovarian reserve, it is necessary to evaluate the follicular density in the ovarian tissue surrounding endometriosis on preoperative imaging. The purpose of the present study was to evaluate the usefulness of subtraction pelvic magnetic resonance imaging (MRI) to detect ovarian reserve. Methods: A subtracted T1-weighted image (^subT1WI) was obtained by subtracting unenhanced T1WI from contrast-enhanced T1WI (^ceT1WI) with similar parameters in 22 patients with ovarian endometriosis. The signal-to-noise ratio (SNR) in ovarian endometriosis, which was classified into the high signal intensity and iso-to-low signal intensity groups on the T2-weighted image, was compared to that in normal ovarian tissue. To evaluate the effect of contrast enhancement, a standardization map was obtained by dividing ^subT1WI by ^ceT1WI. Results: On visual assessment of 22 patients with ovarian endometriosis, 16 patients showed a high signal intensity, and 6 patients showed an iso-to-low signal intensity on T1WI. Although SNR in endometriosis with a high signal intensity was higher than that with an iso-to-low signal intensity, there was no difference in SNR after the subtraction (13.72±77.55 vs. 63.03±43.90, p=0.126). The area of the affected ovary was smaller than that of the normal ovary (121.10±22.48 vs. 380.51±75.87 ㎟, p=0.002), but the mean number of pixels in the viable remaining tissue of the affected ovary was similar to that of the normal ovary (0.53±0.09 vs. 0.47±0.09, p=0.682). Conclusion: The subtraction technique used with pelvic MRI could reveal the extent of endometrial invasion of the normal ovarian tissue and viable remnant ovarian tissue.

• The Journal of the Acoustical Society of Korea
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• v.23 no.2
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• pp.180-186
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• 2004

The presence of noise in speech signals degrades the performance of recognition systems in which there are mismatches between the training and test environments. To make a speech recognizer robust, it is necessary to compensate these mismatches. In this paper, we studied about an improvement of stochastic feature extraction based on band-SNR for robust speech recognition. At first, we proposed a modified version of the multi-band spectral subtraction (MSS) method which adjusts the subtraction level of noise spectrum according to band-SNR. In the proposed method referred as M-MSS, a noise normalization factor was newly introduced to finely control the over-estimation factor depending on the band-SNR. Also, we modified the architecture of the stochastic feature extraction (SFE) method. We could get a better performance when the spectral subtraction was applied in the power spectrum domain than in the mel-scale domain. This method is denoted as M-SFE. Last, we applied the M-MSS method to the modified stochastic feature extraction structure, which is denoted as the MMSS-MSFE method. The proposed methods were evaluated on isolated word recognition under various noise environments. The average error rates of the M-MSS, M-SFE, and MMSS-MSFE methods over the ordinary spectral subtraction (SS) method were reduced by 18.6%, 15.1%, and 33.9%, respectively. From these results, we can conclude that the proposed methods provide good candidates for robust feature extraction in the noisy speech recognition.

• Journal of the Korean Society of Radiology
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• v.17 no.1
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• pp.157-165
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• 2023

Ultrasound imaging uses sound waves of frequencies to cause physical actions such as reflection, absorption, refraction, and transmission at the edge between different tissues. Improvement is needed because there is a lot of noise due to the characteristics of the data generated from the ultrasound equipment, and it is difficult to grasp the shape of the tissue to be actually observed because the edge is vague. The edge enhancement method is used as a method to solve the case where the edge surface looks clumped due to a decrease in image quality. In this paper, as a method to strengthen the interface, the quality improvement was confirmed by strengthening the interface, which is the high-frequency part, in each image using an unsharpening mask and high boost. The mask filtering used for each image was evaluated by measuring PSNR and SNR. Abdominal, head, heart, liver, kidney, breast, and fetal images were obtained from Philips epiq5g and affiniti70g and Alpinion E-cube 15 ultrasound equipment. The program used to implement the algorithm was implemented with MATLAB R2022a of MathWorks. The unsharpening and high-boost mask array size was set to 3*3, and the laplacian filter, a spatial filter used to create outline-enhanced images, was applied equally to both masks. ImageJ program was used for quantitative evaluation of image quality. As a result of applying the mask filter to various ultrasound images, the subjective image quality showed that the overall contour lines of the image were clearly visible when unsharpening and high-boost mask were applied to the original image. When comparing the quantitative image quality, the image quality of the image to which the unsharpening mask and the high boost mask were applied was evaluated higher than that of the original image. In the portal vein, head, gallbladder, and kidney images, the SNR, PSNR, RMSE and MAE of the image to which the high-boost mask was applied were measured to be high. Conversely, for images of the heart, breast, and fetus, SNR, PSNR, RMSE and MAE values were measured as images with the unsharpening mask applied. It is thought that using the optimal mask according to the image will help to improve the image quality, and the contour information was provided to improve the image quality.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.8
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• pp.1665-1674
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• 2011

In this paper, we proposed an algorithm for speech enhancement of speeches corrupted by colored noise. When there is no correlation between colored noise and speech signal, the colored noise turns into white noise through whitening transformation. This transformed signal has been applied to the generalized subspace approach for speech enhancement. The speech spectral distortion, produced by the whitening transformation as pre-processing, has been restored by using the inverse whitening transformation as post-processing of the proposed algorithm. The performance of the proposed algorithm for speech enhancement has been confirmed by computer simulation. The colored noises used in this experiment were car noise and multi-talker babble. It is confirmed that the proposed algorithm shows better performance from SNR and SSD viewpoint over the previous approach with the data from the AURORA and TIMIT data base.

• The Journal of the Acoustical Society of Korea
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• v.23 no.7
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• pp.540-547
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• 2004

Since speech enhancement algorithms based on Kalman/Wiener filter require a priori knowledge of the noise and have focused on the minimization of the variance of the estimation error between clean and estimated speech signal, small estimation error on the noise statistics may lead to large estimation error. However, H/sub ∞/ filter does not require any assumptions and a priori knowledge of the noise statistics, but searches the best estimated signal among the entire estimated signal by applying least upper bound, consequently it is more robust to the variation of noise statistics than Kalman/Wiener filter. In this paper, we Propose a speech enhancement method using HMM and multi H/sub ∞/ filters. First, HMM parameters are estimated with the training data. Secondly, speech is filtered with multiple number of H/sub ∞/ filters. Finally, the estimation of clean speech is obtained from the sum of the weighted filtered outputs. Experimental results shows about 1dB∼2dB SNR improvement with a slight increment of computation compared with the Kalman filter method.